Formulas to Forecast Blogger, YouTube & Influencer ROAS

If you’re reading this post you’ve been asked to forecast revenue (ROAS, return on ad spend) or a return on investment from influencers, YouTubers and bloggers.  It can seem tricky at first, but it is fairly simple. You just need to collect accurate data points to plug into the formulas below.  Then you can fine tune the formulas to work specific to your campaign goals once you have real world data to modify them with.

This post is divided into three sections:

1. Collecting the data to use in the forecast
2. Knowing which variables will throw numbers off
3. The formulas

Before we start I want to mention an important talking point I said at State of Search.

“You need to match your products to the influencer’s audience and not the influencer’s audience to your campaign goals.”

The influencer cannot magically make their audience become “married with children” or “single with large dogs living in urban condos”.  Influencers and bloggers (with readership) have audience demographics that will or will not be influenced to buy.

If you do not match your campaign theme to talk directly to that audience, and your products do not meet that specific audiences’ needs, then nobody will take action and your campaign will not succeed.

If magically the audience does respond to an irrelevant product or campaign by clicking like and leaving comments about how they’re excited to purchase, you have now discovered who is using pods and buying fake metrics to scam people like you into giving them money.  There is always a chance it is real, and you’ll be able to tell by looking at the sales numbers that match.

Now lets jump into the formulas since that is what you’re here for.

Collecting Accurate Data Points

The data points to forecast influencer ROI come from other marketing channels and your internal analytics.

You will need as much of the following as you can get:

• Conversion data as a category or by product and sorted by audience demographics (gender, age. zipcode, etc…) from:
  • Analytics
  • Keyword clusters from PPC if you’re doing a blogger campaign
  • Social media ads if you’re using specific channels (New to file customers and non-subscribers for more accurate results)
  • Organic social media (Non follower and non subscriber is better as everything else throws your numbers off.)
• Conversion rates (CR) from each of the above.
• Average Order Value (AOV) from each of the above.
• The average click throughs or visitors by 1,000 impressions, 100 comments, or 100 likes from new-to-file or non-subscriber/follower customers if available.
  • This is for social media and tube influencers, not bloggers.
• Life Time Value (LTV) of the specific demographic or new to file customer that shops for the product you’re promoting.

We can get a lot more detailed if we need to, but that isn’t as important for right now.

Knowing Which Variables Can and Should Not Be Used

Next you need to know which variables are correct and which are not.

• Coupon codes for tracking – If you use coupon codes for tracking influencers or social campaigns, type your “store name + coupons” (i.e. macys coupons, home depot coupon code) into Google and click to reveal all codes on the coupon websites. If any of the influencer or social media tracking codes appear on the site your metrics are wrong.The coupons are being shown to customers from all channels and not that specific influencer or social media campaign.  Eliminate these campaigns, coupons and influencers from your dataset.
  • Bonus-tip: If a Twitter, TikTok, Facebook or other coupon based campaign is still tracking sales after a couple days, chances are you’ll find the codes here. This is why it appears the influencer, campaign or even email blast you sent to your own customers is working so well.  It isn’t working, it is a shopping cart interception throwing off your attribution.
• Reviews – Type store + reviews into Google (i.e. Lowes Reviews or Nordstrom Reviews) and look to see what sites, videos and content shows up.  If YouTube videos show up that use affiliate links, UTM paramaters or coupon codes for your brand + reviews, these are also throwing your numbers off as they are from branded traffic via SEO and people already in the shopping process. Not influencers or bloggers bringing you top funnel traffic and exposure.
• Browser extensions – The last thing to do is download a few of the popular cash back browser extensions.  When you get to checkout click to reveal all available codes and make sure that none of the codes from the dataset you’re using appear in the plugins. Having the codes in the plugins will make your data sets unreliable as it is the toolbar intercepting all channels and not the influencer, blogger or campaign driving the sale.

And now you’re ready to forecast YouTube, blogger and influencer ROI and ROAS numbers!

Formulas to Forecast Influencer ROAS, YouTubers and Bloggers

Below you will find two basic formulas, but as a fair warning I do not remember the proper order of operations (addition, division, FOIL, etc…). Because of this I’ve included the written instructions, then the formula and then how to plug in the information.  I will modify the formulas so they follow proper mathematical functions once this post is live, so give me some time.

YouTube and Bloggers ROI Formula

1. Take the average views per new video and multiply by XY% of this (I use 15% in the example below, but from my experience it is lower) for the percentage of people that scroll below the video or title to click a link. This will give you how much traffic you can expect in a perfect scenario.
   • The actual Click Through Rate (CTR) depends on how well the YouTuber or Blogger pre-sells the products and directs the end user to the call to action.
2. Next we look at the conversion rate and AOV from SEO and PPC and apply it since YouTube is very similar in search queries and Bloggers can rely on SEO traffic.
3. Now we take the average/median of the above AOVs and combine with our demographic AOV and conversion rates for the same product or category of products.
4. The fourth step is to match these demographics to the audience demographics from the influencers YouTube channel or the most recent 15 posts on the blogger’s site and/or their newsletter list.
   • If this is a blogger you do not want sitewide demographics.  You want the demographics of the newsletter list as this is their actual reader base that comes back, and/or their most recent 15 posts which can be found in Google Analytics. Site demographics can include one time only visitors from Google and social media who never come back and will never see your post on their blog.
5. Last we multiple by the Life Time Value (LTV) of the customer.

The formula:

(Views * 15%) + ((AOV SEO/PPC + AOV Demographics) /2) X CR * = ROAS

Example:

An influencer on YouTube has 1,000 average views per new video. Our conversion rate is 2% with an AOV of $100 for both demographics and PPC/SEO.  This demographic shops 5 times with us on average before not coming back.

The ROAS forecast is:

(1000 * .15) * .02 *$100 * 5 = $1,500

Influencer ROAS Formula

Please note that each platform has limitations and advantages.

• Twitter has clickable links and hashtags
• Instagram/SnapChat, etc… do not have easily clickable links so they need coupon codes.
• TikTok is massive for decision making but tracking via links can be tricky and you need cross device set up.
• Pinterest has clickable links but very low engagement for new pins as it is algorithmically based so it can be evergreen.

1. Take the average likes, repins, retweets, etc… per new share (or impressions) and multiply by the % of visitors to your site by new share by platform.
   • Reminder – this comes from our non-subscriber data from the social ads we run on that platform (eliminate repeat customers and followers).
2. Now take the AOV and CR from our demographic data based on step 1 and match it to the audience demographics provided by the influencer.
3. Last we multiple by the Life Time Value (LTV) of the customer.

The Formula:

(Engagements/impressions per new share * % of visitors that come through) + AOV Demographics * CR * LTV = ROAS

Example:

An influencer has 100 retweets and 50 hearts resulting in 10,000 impressions.  There is a 1% click through on XY product that uses a video + hashtag like ABC. Our AOV and conversion rates are $120 and 4% for the demographic audience match.  This same audience has an LTV of 6 shopping trips with us.

Formula:

(10,000 * .01) * 4% * $120 * 6 = $2,880

And now you know or have a starting point for how to forecast ROI for influencers, YouTubers and Bloggers.